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Precomputed shape-recognition sensitivity results (demo)

Source: R/shape_sensitivity_demo-doc.R
shape_sensitivity_demo.Rd

Raw output from a small-footprint invocation of janusplot_shape_sensitivity(). Shipped so users can explore the sensitivity API and regenerate every figure in the shape-recognition-sensitivity vignette without having to re-run the sweep themselves. Regenerated via data-raw/shape_sensitivity_demo.R.

Design:

  • Shapes (6, one per non-degenerate archetype): linear_up, concave_up, u_shape, inverted_u, wave, bimodal.

  • Sample sizes (3): c(100, 200, 500).

  • Noise levels (4): c(0.05, 0.10, 0.20, 0.40) fraction of y-range.

  • Replicates: 30.

  • Total fits: 2160.

  • Seed: 2026.

Usage

shape_sensitivity_demo

Format

A data frame with 2160 rows and 14 columns — see the "Value" section of janusplot_shape_sensitivity() for the column schema.

See also

janusplot_shape_sensitivity(), janusplot_shape_sensitivity_plot(), janusplot_shape_sensitivity_summary().

Examples

data("shape_sensitivity_demo", package = "janusplot")
head(shape_sensitivity_demo)
#>        truth   n sigma seed  predicted correct archetype_truth  archetype_pred
#> 1  linear_up 100  0.05 2027  linear_up    TRUE monotone_linear monotone_linear
#> 2 concave_up 100  0.05 2028 concave_up    TRUE monotone_curved monotone_curved
#> 3    u_shape 100  0.05 2029    u_shape    TRUE        unimodal        unimodal
#> 4 inverted_u 100  0.05 2030 inverted_u    TRUE        unimodal        unimodal
#> 5       wave 100  0.05 2031 broad_peak   FALSE            wave        unimodal
#> 6    bimodal 100  0.05 2032    bimodal    TRUE      multimodal      multimodal
#>   archetype_correct monotonicity_index convexity_index n_turn n_inflect error
#> 1              TRUE         1.00000000       0.0000000      0         0  <NA>
#> 2              TRUE         1.00000000      -0.8465475      0         0  <NA>
#> 3              TRUE         0.11665809       1.0000000      1         0  <NA>
#> 4              TRUE         0.15257336      -1.0000000      1         0  <NA>
#> 5             FALSE        -0.01095819      -0.3279191      1         2  <NA>
#> 6              TRUE        -0.07937189      -0.2582627      3         2  <NA>
janusplot_shape_sensitivity_plot(shape_sensitivity_demo,
                                 "recovery_curves")